Lesion volume and spike frequency on EEG impact perfusion values in focal cortical dysplasia: a pediatric arterial spin labeling study

Arterial spin labelling (ASL), an MRI sequence non-invasively imaging brain perfusion, has yielded promising results in the presurgical workup of children with focal cortical dysplasia (FCD)-related epilepsy. However, the interpretation of ASL-derived perfusion patterns remains unclear. Hence, we compared ASL qualitative and quantitative findings to their clinical, EEG, and MRI counterparts. We included children with focal structural epilepsy related to an MRI-detectable FCD who underwent single delay pseudo-continuous ASL. ASL perfusion changes were assessed qualitatively by visual inspection and quantitatively by estimating the asymmetry index (AI). We considered 18 scans from 15 children. 16 of 18 (89%) scans showed FCD-related perfusion changes: 10 were hypoperfused, whereas six were hyperperfused. Nine scans had perfusion changes larger than and seven equal to the FCD extent on anatomical images. Hyperperfusion was associated with frequent interictal spikes on EEG (p = 0.047). Perfusion changes in ASL larger than the FCD corresponded to larger lesions (p = 0.017). Higher AI values were determined by frequent interictal spikes on EEG (p = 0.004). ASL showed FCD-related perfusion changes in most cases. Further, higher spike frequency on EEG may increase ASL changes in affected children. These observations may facilitate the interpretation of ASL findings, improving treatment management, counselling, and prognostication in children with FCD-related epilepsy.


Clinical features
Fifteen children (60% male, Supplementary Fig. 1) with a median age at MRI of 11.5 years (interquartile range, IQR: 2.0-13.7;age < 6 years in 6 cases) and median epilepsy duration of 1.1 years (IQR: 0.8-4.5)were included in our study (Table 1).All patients were MRI-positive; we only considered MRI scans acquired before surgery for our analysis.Seven of 15 (47%) children underwent epilepsy surgery.Histopathology verified FCD I in three cases, FCD II in three cases, and FCD III in one case.Details regarding the lesion characteristics in all patients, including those who underwent epilepsy surgery, are provided in Supplementary Table 1.
All children underwent MRI, including ASL, at one (N = 12) or two (N = 3) different time points due to clinical indication.Thus, 18 MRI scans and the corresponding EEG recordings (seven in wakefulness and 11 both in wakefulness and sleep) were considered for analysis.The median latency between the MRI and EEG acquisition was ± 14 days (IQR: 3-61); seven (39%) of EEGs were acquired within seven days from the MRI.

EEG characteristics
The median EEG duration was 87 min (IQR: 46-2156 min) and exceeded 24 h in eight of 18 cases.Focal slowing was detected in 11 of 18 (61%) EEGs.Spikes were detected in 15 of 18 (83%) EEGs; these were frequent in eight cases (Table 1).Focal slowing and spikes colocalised with the FCD in anatomical images and the perfusion changes in ASL in all cases (Supplementary Table 1).

MRI qualitative analysis
Of 15 FCDs, 8 (53%) were left-sided; eight were frontal, three temporal, three posterior, and one multilobar.Six FCDs were deep-seated: two mesial temporal, one fronto-basal, and three mesial parietal (Table 1).16 (89%) scans showed perfusion changes ipsilateral to the FCD: 10 were hypoperfused, whereas six were hyperperfused compared to the contralateral brain parenchyma (CBP); nine had perfusion changes larger than the FCD extent, and seven had perfusion changes equal to the FCD extent.In two of three cases scanned twice, the perfusion pattern remained constant, while in one case, the perfusion pattern changed between hyper-and hypoperfused.In all cases with repeat scans, the extent of the perfusion changes remained consistent.The two cases lacking FCD-related perfusion changes did not differ from the other cases as to their clinical, EEG, or anatomical MRI features (Table 2).A hypoperfused pattern was noted in six of ten (60%) scans acquired under sedation and in four of eight (50%) scans acquired without sedation (Supplementary Table 1).
Hyperperfusion in ASL was associated with frequent spikes in EEG (p = 0.047, Chi-square test), and perfusion changes in ASL larger than the FCD on anatomical images corresponded to larger lesion volumes (p = 0.017, Wilcoxon-Mann-Whitney test).No other epilepsy-related or lesion-related features significantly impacted the respective perfusion changes (Tables 2, 3).
Higher AI values were associated with frequent spikes in EEG (p = 0.004, Welch t-test, Fig. 2A).In the univariate analysis, smaller FCD volumes showed a statistical trend of being correlated with higher AI values after controlling for age at MRI (Spearman's correlation: − 0.48, p = 0.05, Fig. 2B), whereas other epilepsy-related or lesion-related features were not related to AI values (Table 4).Frequent spikes retained their significance as an independent predictor of higher AI values in the multivariate analysis even after correcting for lesion volume (adjusted R 2 : 0.31, p = 0.03, Supplementary Table 2).Table 1.Clinical features, EEG and MRI findings, and histopathology.We used per-patient analysis to detail the overall clinical features of the patients, and per-scan analysis to describe the respective EEG and MRI findings.Lobar involvement was classified as frontal, temporal, posterior, and multilobar.Lesions located in the parietal or occipital lobe were grouped as posterior, while lesions defined as multilobar involved more than one lobe, irrespective of the lobes involved.n: Number; FCD: Focal cortical dysplasia; MRI: Magnetic resonance; ASM: Anti-seizure medication; IQR: Inter-quartile range; Posterior: Involving either the parietal or the occipital lobe; *: Seizure free in the year before the MRI.

Discussion
To our knowledge, this is the largest study to evaluate the perfusion changes captured by ASL in children with FCD-related epilepsy and to investigate their determinants.ASL showed FCD-related perfusion changes in all but two cases.In the qualitative analysis, the FCD-related hyperperfusion pattern was determined by frequent focal spikes but not by focal slowing in EEG, while larger FCD-related perfusion changes corresponded to larger lesion volumes in anatomical MRI.In the quantitative analysis, higher AI values were associated with frequent spikes after correcting for lesion volume.These observations may facilitate the interpretation of ASL findings in children with FCD-related epilepsy and thus improve treatment management, counselling, and prognostication.All but two scans showed FCD-related perfusion changes in our study, corroborating previous findings from small-size, predominantly frontal lobe epilepsy case series 24,27,28,30 in a larger cohort, representative for temporal and extratemporal epilepsy, deep-seated and superficial lesions, and the entire paediatric age range.It should be noted that FCD-related perfusion changes were detectable on ASL despite sedation in half of our cohort, in contrast with the only previous study focusing on ASL in FCD-related epilepsy, which considered exclusively scans performed without sedation 30 .This observation is encouraging, considering the young age at epilepsy onset and the impaired cognitive functioning in children undergoing presurgical evaluation 11,[13][14][15][34][35][36][37][38] -and requiring sedation for MRI acquisition-along with the benefits of early referral and, if indicated, early surgical intervention in this vulnerable population 16 .
FCD-related hyperperfusion, observed in one-third of scans in our study, correlated with frequent EEG spikes but not with other epilepsy-related features.This lack of correlation between specific perfusion patterns and clinical or imaging features mirrors a recent PET study in temporal lobe epilepsy 39 .Commonly, hyperperfusion in FCD has been attributed to seizure activity, focally or regionally increasing the CBF 40 .However, hyperperfusion has been shown to persist for days to weeks after the resolution of the ictal state 22,41,42 , particularly after prolonged or repetitive seizures, suggesting a more complex correlation with brain activity.A recent study in pediatric lesional epilepsy linked frequent spikes to hypermetabolic patterns in PET, suggesting that a state of increased regional epileptogenicity may contribute to increased regional metabolism 43 .Interestingly, in this   www.nature.com/scientificreports/cohort of histopathologically verified FCD-associated epilepsy, only a few patients (13%) had clinical or subclinical seizures during their PET/EEG evaluation 43 .Repetitive epileptic discharges, the characteristic interictal EEG pattern mirroring the high intrinsic epileptogenicity of FCD 44 , may underlie perfusion changes, suggesting an ictal state, increasing the visibility of perfusion changes in ASL.ASL revealed FCD-related hypoperfusion in studies involving older children and adults 29,30 , but FCD-related hyperperfusion in a case series involving infants and toddlers 28 .Although hyperperfusion was not exclusive to the younger patients or earlier stages of the disease in our study, the timing of ASL acquisition may still play a role.Neuronal hyperexcitability may induce functional and metabolic changes leading to CBF increase at epilepsy onset 29 , whereas loss of neurons and gliosis over time may induce neuronal functional and metabolic isolation 45 , as reported in local field potential studies, leading to CBF decrease 46 .This pathophysiological mechanism may also explain the change in perfusion pattern observed in one of three children scanned twice in our study.Finally, it should be noted that irrespective of the perfusion pattern corresponding to the epileptogenic lesion, perfusion changes point to abnormal activity, constituting a valuable indicator of the epileptogenic zone.FCD-related perfusion changes in ASL more extensive than the anatomical lesions, observed in one-half of scans in our study, correlated with larger lesion volume but not with other epilepsy-related or lesion-related features.This observation is not surprising since larger epileptogenic lesions are intuitively expected to result in a larger functional disruption and, thus, more extensive perfusion changes.However, this finding is encouraging since larger lesions, the trademark of paediatric epilepsy surgery 10,36 , predispose to earlier epilepsy onset and a more severe epilepsy course, were less likely to have ever been reported MRI-negative, and more likely to have undergone epilepsy surgery in a recent large multicentric study 47 .Interestingly, our study is the first to investigate the effect of lesion volume on the visibility of perfusion changes imaged by ASL since previous studies focused mainly on the colocalisation of the perfusion changes with the anatomical lesions at the gyral or lobar scale 24,29,30 .Although the presence of perfusion changes beyond the MRI-visible lesion may correspond to a more subtle-and thus less clearly discernible-part of the cortical malformation, it should be noted that focal lesional epilepsy is a network disease, often involving widespread connections beyond the seizure onset zone and the epileptogenic lesion 45,48,49 .This concept has been previously established in PET studies, where metabolic changes usually extend beyond the epileptogenic lesions, particularly in temporal lobe epilepsy 39 .Perfusion changes may thus be perceived as a marker of the epileptic network, accounting for the stability of ASL findings in children scanned twice in our study.Advanced techniques, such as ASL, expand the potential of MRI beyond mere lesion identification, contributing to the non-invasive delineation of affected brain tissue within the often more extensive epileptic network 45 , supporting hypotheses based on electro-clinical correlations, and guiding successful surgical intervention.
Higher AI values were determined by frequent EEG spikes after correcting for lesion volume, corroborating the results of expert-driven visual analysis by using the data-driven standardised and reproducible AI measure.Of note, a PET study in temporal lobe epilepsy reported a high correlation between the number of interictal spikes recorded in temporal EEG electrodes and the AI values, reflecting the metabolism imaged by PET in the temporopolar regions 50 .Our study corroborates the observation of a link between EEG and brain metabolism, as imaged by PET, and extends it to a link between EEG and brain perfusion, as imaged by ASL, highlighting the opportunities offered by modern imaging tools in the presurgical evaluation of paediatric lesional epilepsy.In this setting, AI offers several advantages over the visual-only evaluation of perfusion maps, contributing to higher FCD-detectability and concordance rates with other tools, such as EEG, MRI, and PET, in detecting the epileptogenic zone 25 .By facilitating the standardisation of perfusion values across patients, AI can counteract the effects of other potential confounders, such as age or sedation, as evidenced by our study.Thus, voxelwise approaches of AI calculation highlighting perfusion asymmetries between the hemispheres have been www.nature.com/scientificreports/increasingly implemented in the latest ASL studies 25,31 to obtain observer-independent results and increase confidence in image reporting.The recent observation that specific interictal spike patterns in presurgical EEG are predictive of postsurgical seizure freedom in FCD-associated epilepsy 51 , gives additional weight to the link between ASL and interictal spikes substantiated for the first time in our study, pointing to exciting avenues of ASL application beyond the obvious benefits for image reporting and lesion detection.
Although EEG simultaneous to the ASL acquisition should facilitate the differentiation between interictal and ictal ASL findings, this setup has been available in only one small-size study so far and has added no value over other presurgical modalities with less time-consuming recording and analysis 31 .Despite these sparse and disappointing results, EEG-guided image analysis may still add to the diagnostic value of each modality alone by aligning ASL perfusion changes with EEG signal modifications and enabling their interpretation.
Future studies in larger and homogeneous paediatric FCD-related epilepsy cohorts are expected to shed some light on the ASL features and their potential in the particularly challenging subgroup of MRI-negative cases.In contrast to the overall poor yield of visual ASL analysis in MRI-negative FCD-related epilepsy 24,25 , the increasingly implemented quantitative ASL analysis has so far shown promising results 25,31 .It remains to be investigated if the findings derived from our MRI-positive FCD cohort are applicable to MRI-negative cohorts.
Considering that the spiking rate in EEG increases in sleep, particularly in the N2 and N3 sleep stages, in the majority of focal epilepsy patients 52 , long-term EEG recordings capturing these sleep stages 45 are more suitable to investigate the correlation of frequent spikes on EEG with perfusion changes on MRI.The availability of longer data segments including all vigilance states across all patients would help overcome the limitations of our study, partly drawing from shorter recordings, and offer a more detailed insight into this intriguing correlation of epileptic activity and brain perfusion.

Conclusion
Our study confirmed that most FCD generate perfusion changes on ASL images.Hyperperfused FCD correlates with a higher spike rate, likely reflecting a higher degree of epileptogenicity.Moreover, larger lesions commonly induce more extensive perfusion changes, mirroring a more extensive epileptogenic network.Finally, higher AI values also relate to higher spike rates in EEG.In addition to facilitating the interpretation of ASL findings, connecting interictal epileptic activity with brain perfusion opens promising perspectives for the future clinical and research implementation of ASL in paediatric epilepsy studies.In the clinical setting, our observations foster the introduction of ASL in imaging protocols, potentially improving treatment management, counselling, and prognostication in children with FCD-related epilepsy.In the research field, ASL findings may provide a new biomarker in this patient subgroup and a valid addition to automatic FCD detection tools.

Patient selection
We included children and adolescents who underwent brain MRI between January 2017 and March 2023 at the University Children's Hospital Zurich, according to our dedicated epilepsy protocol 10,15,34,36,[53][54][55] .The inclusion criteria were: (1) age ≤ 19 years at the time of the MRI, (2) diagnosis of focal structural epilepsy, according to seizure semiology, EEG, and MRI findings, (3) diagnosis of FCD according to radiological criteria 56,57 , corroborated by histopathology in surgical cases 58 , (4) no history of prior resective epilepsy surgery, and (5) availability of ASL MRI sequences.We excluded MRI scans with overall poor quality (Supplementary Fig. 1).The collection of patient data and their analysis were approved by and performed according to the guidelines and regulations of the local ethics committee (Kantonale Ethikkommission Zürich, KEK-ZH 2024-00298).Informed consent was obtained from all subjects and/or their legal guardian(s).

EEG acquisition and analysis
EEGs were acquired with 21 electrodes placed according to the international 10-20 system by the Micromed® (Mogliano Veneto, Treviso, Italy) or Deltamed® (Paris, France) recording systems.The EEG concurrent to each MRI was visually reviewed by a fully trained EEG technician and a fully trained neurologist, blinded to the clinical report.Discrepancies were resolved by consensus.EEGs in wakefulness and/or sleep were analysed depending on their availability.Sleep staging was performed according to the American Academy of Sleep Medicine (AASM) guidelines 59 .The presence of focal slowing and spikes was noted.These parameters were selected based on previous work suggesting a correlation between focal slowing and ASL perfusion changes in tuberous sclerosis 60 , and between spikes and ASL perfusion changes in temporal lobe epilepsy 61 .Spike frequency was calculated considering all spikes noted in the first hour of wakefulness and in the first hour of non-rapid eye movement (NREM) sleep, where applicable 62 and dichotomized 63 in "frequent" at ≥ 60 spikes per hour and "non-frequent" at < 60 spikes per hour.

MRI acquisition
All MRI scans were acquired on a 3 T scanner (Discovery MR 750 or Signa Premier, GE Medical Systems, WI, USA), using an 8-channel coil 34,54,55 .Anatomical and perfusion images (ASL) were acquired in all cases.Parameters for anatomical image acquisition have been provided in our previous work 53 , while those for ASL acquisition were: pseudo-continuous ASL, echo time 10.5-11.2ms, repetition time 4531-4742 ms, single post labelling delay of 1525 ms, flip angle 111°, averages 3, slice thickness 4 mm, spacing between slices 4 mm, and spiral readout.Quantitative perfusion maps were automatically generated by GE reconstruction software.Children underwent sedation if clinically indicated 26 .Since no clinical seizures were noted during the MRI scan, the perfusion patterns shown by the scans were considered to mirror the brain perfusion during the interictal state.

Figure 1 .
Figure1.MRI analysis pipeline of anatomical and perfusion images.A. Qualitative analysis.The perfusion changes corresponding to the focal cortical dysplasia (FCD) were characterised as hyperperfused, isoperfused, or hypoperfused compared to the contralateral brain parenchyma (CBP).The extent of the perfusion changes corresponding to the FCD was characterised as "larger" or "equal" compared to the lesion extent in anatomical images.B. Quantitative analysis.Anatomical images (volumetric T1-weighted and FLAIR) were used for lesion segmentation.Segmentations were manually drawn by the same radiologist who performed the qualitative analysis, encompassing the signal intensity changes visible on anatomical images.Both grey and white matter were included in the polygonal, volumetric region of interest (ROI).Dilation-erosion and smoothing algorithms were used to minimise segmentation errors.Before saving the segmentation as a binary label, the ROI position was carefully checked against that of the brain gyri and adjusted as needed.FSL (www.fmrib.ox.ac.uk/ fsl) was used to co-register T1-weighted images to ASL by rigid body registration.Subsequently, T1-weighted images were co-registered to the MNI152 atlas, extending the co-registration process to ASL images and binary labels.The perfusion values were computed by extracting the mean cerebral blood flow (CBF) values within the binary labels.The CBF values were first calculated within the binary label deriving from the FCD and then within the flipped label corresponding to the CBP.CBF: cerebral blood flow; CBP: contralateral brain parenchyma; FCD: focal cortical dysplasia.

Figure 2 .
Figure 2. Higher Asymmetry Index (AI) values related to frequent spikes in EEG and by smaller lesion volumes.(A) Higher asymmetry index (AI) values were determined by frequent interictal spikes (≥ 60 spikes/h, n = 8; < 60 spikes/h, n = 10) on electroencephalography (EEG, p = 0.004, Welch t-test).The bar plot illustrates the AI values' mean and standard deviation, depending on frequent spikes on interictal EEG.(B) The scatterplot illustrates the correlation between the AI values and the focal cortical dysplasia (FCD) volume when controlled for age at MRI.The data points are colour-coded according to the age at MRI. Smaller FCD volumes showed a statistical trend of being correlated with higher AI values after controlling for age at MRI (Spearman's correlation: − 0.48, p = 0.05).AI: asymmetry index; EEG: electroencephalography; FCD: focal cortical dysplasia; h: hour; y: years.

Table 2 .
Hyperperfusion patterns in arterial spin labelling (ASL) are determined by frequent spikes in EEG.Perfusion patterns in the ASL are provided in relation to clinical features, EEG, and anatomical MRI findings.y: years; FCD: Focal cortical dysplasia; IQR: Inter-quartile range; # : Chi-square test; $ : Kruskal Wallis test; *Statistical significance. CLINICAL,

Table 4 .
Higher Asymmetry Index (AI) values are determined by frequent spikes and smaller focal cortical dysplasia (FCD) volumes.The AI values are provided in relation to clinical features, EEG and anatomical MRI findings.y: years; FCD: Focal cortical dysplasia; SD: Standard deviation; # : Welch t-test; $ : Spearman's correlation; *Statistical significance.